A Layered Control Architecture for Collision-Free Vehicle Coordination at Signal-Free Intersections Using SUMO and ROS2

Signal-free intersections enhance traffic efficiency and safety using Connected and Automated Vehicles (CAVs), yet existing methods struggle with computational complexity and real-time demands. This paper introduces a three-layer control architecture for seamless vehicle coordination. The server layer optimizes global traffic flow via dynamic priority adjustments, the road side unit (RSU) layer ensures local coordination through time slot allocation, and the vehicle layer employs sliding mode control for precise trajectory tracking. Integrated with SUMO and ROS2 via TraCI, it enables real-time cooperation in CAV control. Simulations at 1500 vehicles/hour show a 100% reduction in waiting time (from 1.60 s to 0 s) and albeit with a 17% travel time increase (from 62.96 s to 73.73 s) due to safety-driven speed adjustments. This scalable framework of coordination advances CAV intersection management for real-world deployment.

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Publication Details

Published
2025-05-17
DOI
https://doi.org/10.1109/yac66630.2025.11149992
Primary Topic
Aquatic Ecosystems and Phytoplankton Dynamics
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article
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article

A Layered Control Architecture for Collision-Free Vehicle Coordination at Signal-Free Intersections Using SUMO and ROS2

Aquatic Ecosystems and Phytoplankton Dynamics
article

A Layered Control Architecture for Collision-Free Vehicle Coordination at Signal-Free Intersections Using SUMO and ROS2

article en

Abstract

Signal-free intersections enhance traffic efficiency and safety using Connected and Automated Vehicles (CAVs), yet existing methods struggle with computational complexity and real-time demands. This paper introduces a three-layer control architecture for seamless vehicle coordination. The server layer optimizes global traffic flow via dynamic priority adjustments, the road side unit (RSU) layer ensures local coordination through time slot allocation, and the vehicle layer employs sliding mode control for precise trajectory tracking. Integrated with SUMO and ROS2 via TraCI, it enables real-time cooperation in CAV control. Simulations at 1500 vehicles/hour show a 100% reduction in waiting time (from 1.60 s to 0 s) and albeit with a 17% travel time increase (from 62.96 s to 73.73 s) due to safety-driven speed adjustments. This scalable framework of coordination advances CAV intersection management for real-world deployment.

Shenyang University of Technology (CN), Dalian University (CN), Dalian Maritime University (CN)
Sustainable cities and communities
Openalex Percentile: Top 50%
Aquatic Ecosystems and Phytoplankton Dynamics
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